ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Division Spotlight
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
Latest Magazine Issues
May 2024
Jan 2024
Latest Journal Issues
Nuclear Science and Engineering
June 2024
Nuclear Technology
Fusion Science and Technology
Latest News
Proving DRACO will deliver
The United States is now closer than it has been in over five decades to launching the first nuclear thermal rocket into space, thanks to DRACO—the Demonstration Rocket for Agile Cislunar Orbit.
Peter L. Angelo
Nuclear Technology | Volume 189 | Number 3 | March 2015 | Pages 219-240
Technical Paper | Criticality Safety | doi.org/10.13182/NT14-44
Articles are hosted by Taylor and Francis Online.
A feedforward artificial neural network (ANN) is constructed using select nuclear criticality excursion experiment data sets from the French Consequences Radiologiques d’un Accident de Criticité (CRAC) and SILENE reactor campaigns. The ability to represent initial spike characteristics by an ANN provides a new method that is aligned to excursion data more directly and to a wider variable data set than traditional analytic approaches. The ANN is configured, trained, validated, and tested to 85 unique highly enriched uranium (HEU) excursion experiments, considering six input variables and two output variables (specific power and energy). The fidelity of the ANN is enhanced by normalizing the input and output data. The trained ANN is then used to determine output values for 19 select Kinetic Energy Water Boiler experiments and 14 additional CRAC excursions not used in the ANN construction. Furthermore, the same trained ANN is also used for an extensive comparison (80 cases) for a combination of uranium concentrations, ramp feed reactivity insertion rates, system volumes, and vertical container sizes. The specific spike energy and power ranges determined are bracketed by published experiment results and are more realistically represented than results derived from well-known analytical methods. The ability to predict initial peak fissions by an ANN does not require determining, a priori, a volume-dependent energy quench parameter (“b”) specific to HEU solutions. The results derived from the ANN can aid in designing realistic emergency planning constructs or criticality accident alarm system hardware placements without undue penalty for fission source term uncertainties. Neither excursion characteristics after the initial spike nor explicit time dependencies are modeled by an ANN at this time. The extension of the methods presented is left for further work.